@inproceedings{cummings-wilson-2019-clark,
    title = "{CLARK} at {S}em{E}val-2019 Task 3: Exploring the Role of Context to Identify Emotion in a Short Conversation",
    author = "Cummings, Joseph  and
      Wilson, Jason",
    editor = "May, Jonathan  and
      Shutova, Ekaterina  and
      Herbelot, Aurelie  and
      Zhu, Xiaodan  and
      Apidianaki, Marianna  and
      Mohammad, Saif M.",
    booktitle = "Proceedings of the 13th International Workshop on Semantic Evaluation",
    month = jun,
    year = "2019",
    address = "Minneapolis, Minnesota, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/add-emnlp-2024-awards/S19-2024/",
    doi = "10.18653/v1/S19-2024",
    pages = "159--163",
    abstract = "With text lacking valuable information avail-able in other modalities, context may provide useful information to better detect emotions. In this paper, we do a systematic exploration of the role of context in recognizing emotion in a conversation. We use a Naive Bayes model to show that inferring the mood of the conversation before classifying individual utterances leads to better performance. Additionally, we find that using context while train-ing the model significantly decreases performance. Our approach has the additional bene-fit that its performance rivals a baseline LSTM model while requiring fewer resources."
}